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The Journal of Applied Research and Technology JART is a bimonthly open access journal that publishes papers on innovative applications, development of new technologies and efficient solutions in engineering, computing and scientific research. JART publishes manuscripts describing original research, with significant results based on experimental, theoretical and numerical work. The journal does not charge for submission, processing, publication of manuscripts or for color reproduction of photographs. JART classifies research into the following main fields: Material Science Biomaterials, carbon, ceramics, composite, metals, polymers, thin films, functional materials and semiconductors.

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The Journal of Applied Research and Technology JART is a bimonthly open access journal that publishes papers on innovative applications, development of new technologies and efficient solutions in engineering, computing and scientific research.

JART publishes manuscripts describing original research, with significant results based on experimental, theoretical and numerical work. The journal does not charge for submission, processing, publication of manuscripts or for color reproduction of photographs. JART classifies research into the following main fields: Material Science Biomaterials, carbon, ceramics, composite, metals, polymers, thin films, functional materials and semiconductors.

Computer Science Computer graphics and visualization, programming, human-computer interaction, neural networks, image processing and software engineering.

Industrial Engineering Operations research, systems engineering, management science, complex systems and cybernetics applications and information technologies Electronic Engineering Solid-state physics, radio engineering, telecommunications, control systems, signal processing, power electronics, electronic devices and circuits and automation.

Instrumentation engineering and science Measurement devices pressure, temperature, flow, voltage, frequency etc. SRJ is a prestige metric based on the idea that not all citations are the same.

SJR uses a similar algorithm as the Google page rank; it provides a quantitative and qualitative measure of the journal's impact. SNIP measures contextual citation impact by wighting citations based on the total number of citations in a subject field. This paper presents an adaptive imaging technique run on a mobile service system for endoscopic image enhancement by using color transform and Gray Level Co-occurrence Matrices GLCM for a single input endoscopy image.

The method is simply deal with the color image channels combination which chose the maximum scalar values of red, green and blue channel images, respectively.

The GLCM subsequently applied for selecting the highest contrast and entropy images of the expanding image series. The enhanced endoscopy image is generated by fusing of the color, contrast and entropy images. We also proposed a service system with medical image retrieval application via quick response code authentication based on the Android operating system, which helps clinicians convenient in using mobile phone and reviewing images of the patient with cost efficiency.

For the mobile technologies are growing rapidly, the mobile service system is installed to connect a Picture Archive and Communication Systems PACS system in hospital and applied for automatic evaluation of colon images screening. The experimental results show the proposed system is efficient for observing gastrointestinal tract polyp. The performance is evaluated and compared with Fujinon intelligent chromo endoscopy enhanced method.. The image enhance-based endoscopies for tumours and polyps diagnosis become popular and influential in recent decades Gross et al.

Gastrointestinal tract GI cancer is a common malignant tumor seen in the clinic and the incidence rate of GI lesion is increasing in most countries. The focal point to improve the survival rate is the diagnosis and treatment at an early stage, such as regular endoscopy examination.

The traditional endoscopy only detects an apart of characteristics of the lesion, even apply magnifying techniques and it is not enough for observing the mucosal blood and pit pattern capillaries Tanaka et al. Therefore, the narrow-band imaging NBI Sharma et al. NBI is a developed technology that uses optical filters for colors sequential illumination and narrows the bandwidth of spectral transmittance Tanaka et al. It allows enhancing the contrast of vascular patterns on the mucosal surface.

NBI enables the observation of the fine capillaries in the superficial mucosa of the gastrointestinal tract. It is a diagnosis device for an easier observation of tissue characterization on surface parts, and capillary orientations become clearer.

FICE system used the pure image processing technique and makes the possible to select the most suitable wavelengths for observing vessels and small tumor.

The aim of this work is to develop an efficiently enhancing of the endoscopy image while the clinical screening, especially for the texture of microvascular and microsurface features. The work is encouraged by the Hirakawa and Simon to develop a convenient digital color filter for computing enhanced endoscopy image.

In Hirakawa and Simon , they combine photographic filter placed over the lens and the color filter array on image sensor induces differences in red, green, and blue channel sensitivities. In contrast to their approach, we replace real filters with pure digital method to generate the corresponding channel images. We applied the color shifting method Wang et al. Our eyes are sensitive to light which lies in a very small region of the electromagnetic spectrum labeled visible light.

The human eye is not capable of seeing radiation with wavelengths outside the visible spectrum. The rendered endoscopy images are definitely lying within the visible light and each image pixel corresponds to a wavelength within the range of nm. The series of shifting color images is generated by modifying the values of chrominance and chroma, but keeps the values of the luminance fixed for each image pixel.

This says, the acquired image pixels could shift to many new colors by modifying the corresponding values of chrominance and chroma within the visible light. To shift the chrominance and chroma of the image pixels is the key idea of this work to generate a series of images from a single input endoscopy image.

The GLCM is adopted for computing and selecting the highest contrast value from the generated series of an endoscopy image. We demonstrate that to apply the second GLCM for shifting images over the different wavelength of the endoscopy images allows, and their variations can lead to discrimination in the texture and details of polys and types. This work is both to increase the efficiency and clearly of polyp observation for fixable endoscopy in gastrointestinal tract.

PACS are comprehensive management systems for diagnostic imaging studies that are increasingly used in hospitals and health care systems. In this paper, we investigate an enhanced method to observe the endoscopy images for vessels, subcutaneous or polyp of the GI tract. The major contribution of this study is to design a fast image processing method which processes on separated color image channels and selects the channel images with highest scalar values.

The images are then applied to clinical GI endoscopy for efficient observing polyp. The technique is simple and fast for the physician to the diagnose and measuring the tumors and non-tumor area. GI endoscopy is an important diagnostic and therapeutic tool in our daily medical practice.

The quality, texture and resolution of the color image acquired from the gastrointestinal endoscopy infuse the physicians to make the decision of abnormal lesions. Images enhancement then became a key component of the modern endoscopic technology. It is a developed technology that uses optical filters for colors sequential illumination and narrows the bandwidth of the spectral transmittance Tanaka et al.

The drawback of NBI is the lacks of a normal light source; the bandwidth of the frequency is narrowed by imaging narrow the scope, and cannot be quickly converted to the other band. It decomposes images by wavelength, then directly produces reconstructed images with enhanced mucosal surface contrast Nakayoshi et al.

The method is efficient and a bit cost-effective to develop; however, Wang et al. In this study, we would like to develop an image enhancement technique based on the concept of virtual chromoendoscopy system for contrast enhancing the images captured by GI fixable endoscopy. For the color enhancement, Jean-Luc et al. Their findings are that the image enhancement outperforms other filter-based enhancement methods on noisy images.

This paper was inspired by Masahito et al. They are based on Grey-Level-Co-occurrence and Local-Binary-Patterns to develop a texture feature extraction method for examination. The color shifting originally is an inherent property of a LCD and the visible light corresponds to a wavelength range of nm, and a color range of violet through red. The white light is a mixture of the colors of the visible spectrum and black is a total absence of light. In LCD display, the angular color uniformity of a display affects the perceived image quality significantly.

Several previous researchers efforts to improve the color uniformity have been based on the compensation of retardation in the wavelength range. They focused on the angular shifts of the primary colors in the visible wavelength range. This paper follows the color shifting method Wang et al. This study aims to enhance the endoscopy images for better screening rate of GI tract diagnosis.

In this paper, we use a standalone medical image retrieval application with Quick Response Code QR-Code Rouillard, authentication based on the Android operating system, which helps doctors to conveniently assess the medical images via mobile phone.

We designed an application based on Android operating system Shabtai et al. The identical procedure has two ways to authenticate, that are typing identity information and scanning the QR-code of identity. On the server, there is an application program interface API which is used to communicate application with the server.

It handles up all requesting, responding information and encoding it to JSON Crockford, format between mobile applications and server. It includes software for examining, constructing and converting DICOM image files, handling offline media, sending and receiving images over a network connection, as well as demonstrative image storage and work list servers. Their functions are authenticating identity; authenticate identity by QR-code, searching identity of the patient, searching identity of the patient by QR-code and daily logging.

The connection between application and server is used in transport layer security TLS Josefsson, , which is currently used to protect data during transportation. The flow chart of Android application is shown in Figure 2. The flow chart of Android application. Figure 3 is data flow chart of API, which is explaining for requesting and responding information.

The data flow chart of API for communication between server and mobile phone. The manager of organization can create user, delete user, build the QR-code of identity with AES encrypt, load medical images of patient to database and check out daily logging. IMEI is a unique 15 digit code upon production on mobile devices and it can checked all known information regarding manufacturer, model type, and country of approval of a handset.

There is a problem during the system encodes cipher to QR-code with AES encrypt, that the cipher cannot be decrypted after decode the QR-code, because the cipher contains the character which is out of code list, and we used Base64 encoding Josefsson, to solve the problem. Base64 encoding is a group of similar binary-to-text encoding schemes that represent binary data in an ASCII string format by translating it into a radix representation. Figure 4 compares Base64 with Non-Base In this section, we first briefly introduce the approach for image expansion of single endoscopy in UV space Wang et al.

Then, we assemble an enhanced color endoscopy image via the ranking method to choice highest scalar values in red, green and blue channels, respectively. Scalar values are quantity defined only by its magnitude within a processing mask. The polyp area of endoscopy image can be evidently distinguished in the proposed ranking method.

All formulae should be numbered with consecutive Arabic numbers within parenthesis. In other words, the formula is to change the values of chrominance and chroma using a linear transform matrix. Then the ranking values are computed rely on the scalar values, which are the edge energy of a set transformed image and can usually be discerned from the gray scale representation of the area alone, which represents the luminance band of the YUV color space.

This section details the selection of a highest contrast endoscopy image from a series of images generated by image expanding in section IV. The visual effect is more clearly proportional to the higher contrast value.

The contrast is the reflecting of the clarity and the degree of texture of an image. We crop an area of the input endoscopy image and then apply the gradient computing for the crop image. The crop area can be used to apply the second order of GLCM method and the contrast values are calculated for the expanded crop images. The GLCM matrix is calculated from the intensity values of the selected crop area. The matrix capture properties of the selected crop area, but they are not directly useful for further analysis.

It is then further used to compute the contrast value. An approach to image fusion in color includes performing image fusion separately and independently on each color channel, then providing the resulting three color channels and a contrast image as a single color image.

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